Postdoc opportunity at the Pennsylvania State University
Pennsylvania State University, Pennsylvania, United States
Start reviewing process: 2 December 2022

The multiscale hydrology, processes and intelligence ( in Civil & Environmental Engineering at the Pennsylvania State University is recruiting multiple postdoc scholars for incoming projects. The research topics include physics-informed machine learning for hydrologic prediction, e.g., streamflow for Southwestern US and floodcasting using machine learning in the context of the National Water Model (NWM). The candidates need to have a strong mathematical and coding background and a solid publication record. Machine learning (ML) experience is preferred although not mandatory. Experiences with process-based geoscientific models will be valuable. The candidates also need to be comfortable with venturing into unknown territories. The scholar will work with state-of-the-art ML algorithms as well as a deep integration between physics and ML, and will likely interact with a large group of researchers. The MHPI is a frontier in the area of ML in hydrology and has been leading many novel developments. If you are interested, please browse our website, publications, and send inquiries to

ps. my internet connectivity may be limited in the next 2 weeks, so my reply may be delayed, but I will reply when I can.


Chaopeng Shen
Associate Professor
Department of Civil and Environmental Engineering
231C Sackett Building
The Pennsylvania State University
University Park, PA 16802
Our group on AGU TV:

Promoting a deep integration between ML and processes, represented in our recent paper on differentiable parameter learning (

Of interest for:
  • Hydrology Focus Research Group
  • Artificial Intelligence & Machine Learning Initiative